The project targets Python data scientists who
- want to present their results more interactively than via Jupyter notebooks, and
- don't know much about website technologies, like HTML, CSS, webframeworks, and
- want to learn and use only the minimum of these technologies,
- want to start with a website template that already contains examples for everything they want to do.
This repository is a template for a webpage with a Python REST backend.
The template contains
- a call to a Python backend,
- styled examples, like
- a list of items with some actions for them (delete, show, filter)
- an object editor
- a chart
- a dropdown
- mathematical formulas
- forms
- hints how to use HTML, CSS, AngularJS, integration of plugins,
- a description of good practices,
- an exercise.
To make the entry barrier for a Python data scientist as low as possible, this template tries to avoid
- all sophisticated features of current front end development (build tools, framework features)
- the extensive use of HTML elements, CSS properties.
AngularJS 1.x
- allows rapid prototyping,
- provides a concise syntax,
- keeps the developer away from technical details (like event handlers),
- low entrance barrier for non-frontend people (if introduced correctly).
This compensates for the disadvantages, e.g.
- low performance for big pages,
- less modularization options.
To keep things as simple as possible.
Simplicity compensates the disadvantages of this approach, hopefully.
To create you own prototype, just fork the repository and change it.
As the project is in a branch with name gh-pages, its contents are automatically
served via Github Pages,
i.e. a local web server is needed only for testing local changes.
A local webserver can be started via docker-compose:
docker-compose up
open http://127.0.0.1:8081
cd backend
workon myvirtenv-python36
pip install -r requirements.txt
python app.py
./test.sh